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Distributed Weight Selection in Consensus Protocols by Schatten Norm Minimization
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DOI：10.1109/TAC.2014.2352773.png)
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Abstract
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In this work we study the weight optimization problem for average consensus protocols by reformulating it as a Schatten norm minimization with parameter p. We show that as p approaches infinity, the optimal solution of the Schatten norm induced problem recovers the optimal solution of the original problem. Moreover, by tuning the parameter p in our proposed minimization, we can simply trade-off the quality of the solution (i.e., the speed of convergence) for communication/computation requirements (in terms of number of messages exchanged and volume of data processed). We then propose a distributed algorithm to solve the Schatten norm minimization and we show that it outperforms the other distributed weight selection methods.
Keywords:
Consensus protocols
distributed optimization
gradient methods
Schatten norm minimization
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